AI in Safety-Critical Engineering: Where It Helps, Where It Doesn’t, and How to Stay in Control

In the world of safety-critical systems, the integration of AI presents both a monumental opportunity and a unique set of challenges. Engineering teams are under pressure to accelerate innovation and manage growing complexity without compromising on safety

 

How do you harness the power and efficiency of AI while maintaining the reliability required for embedded and safety-critical environments?

 

Join our next episode of AI Talk with Kevin Craine, who hosts a panel discussion where we’ll explore: 

• Where AI can safely accelerate engineering in complex and regulated systems
• Practical use cases for AI in engineering across the life cycle
• Using AI to reduce engineering complexity and cognitive load, not replace engineering judgement
• How AI is analysing data from digital twins

Join this episode as we discuss a roadmap for integrating intelligent tools into your development lifecycle, ensuring that your team can improve productivity and decision-making, while maintaining safety and architectural integrity.